ssc - Event discrete simulation with SimPy
[25 July 2014]
Often, experiments with real world systems are high-risk, accompanied by high
costs or not even possible at all. That’s when simulations come into play.
This talk will give a brief introduction into the topic of simulation. By means
of simple examples, it will demonstrate how you can use SimPy to implement
event-discrete simulations and which features SimPy offers to help you doing
Simulation is important for the analysis of complex systems or the analysis of
the impact of certain actions on that systems. They are especially useful if
the actions are potentially harmful or expensive.
Simulation is used in various natural scientific and economic areas, e.g., for
the modeling and study of biological or physical systems, for resource
scheduling and optimization or at the research for the integration of renewable
energies into the power grid (my personal background). The simulated time can
thereby be seen as continuous or discrete (discrete time or discrete event).
In this talk, I want to show why Python is a good choice for implementing
simulation models and how SimPy can help here.
Structure of the talk (20min talking + 5min discussion + 5min buffer):
- Why simulation? (5min)
- History of SimPy (3min)
- How does SimPy work? (9min)
- Conclusion (3min)
In the introduction, I’ll briefly explain what simulation is and motivate, why
it is a useful tool.
The main part will consist of an introduction and demonstration of SimPy. Since
SimPy is now more then ten years old, I’ll first give a quick overview about
its history and development. Afterwards, I’ll explain SimPy’s concepts and
features by means of simple examples.
In the conclusion, I’ll give a short outlook on the future development of
The main goal of this talk is to create awareness that simulation is a powerful
tool in a lot of domains and to give the audience enough information to ease
their first steps.